We are excited to announce the official launch of DeepImplant — a multidisciplinary project that brings together AI, medical imaging, and mixed reality to radically speed up and simplify the design of patient-specific cranial implants. DeepImplant aims to automate CAD modeling so clinicians and technicians can generate personalized implants in just a few seconds without specialist biomechanical knowledge, and to let users verify modeling correctness interactively using mixed reality.
What the project will deliver
- Fast, automated CAD modeling that produces implant-ready geometry in seconds, reducing weeks of work to minutes
- Accessible workflows that hide modeling complexity behind intuitive AI tools so non-expert users can create safe, clinically useful implants
- Mixed reality verification so surgeons and engineers can inspect and validate designs in 3D before manufacturing
- Clinical-ready integration with accepted medical-manufacturing processes to shorten time from imaging to surgery
Selected initial research
- Wodziński, M.; Daniol, M.; Socha, M.; Hemmerling, D.; Stanuch, M.; Skalski, A. (2022). Deep Learning-Based Framework for Automatic Cranial Defect Reconstruction and Implant Modeling. Computer Methods and Programs in Biomedicine. Read
- Wodziński, M.; Daniol, M.; Hemmerling, D. (2021). Improving the Automatic Cranial Implant Design in Cranioplasty by Linking Different Datasets. In: MICCAI 2023 Challenges. Read
- Kwarciak, K.; Wodziński, M. (2023). Deep Generative Networks for Heterogeneous Augmentation of Cranial Defects. In: ICCV 2023 Workshop. Read